631 research outputs found
Proficiency Evaluation of NDE Personnel Utilizing the Ultrasonic Methodology
The measure by which the capability of a nondestructive testing (NDT) inspector can be assessed is based upon the proficiency by which that particular individual can perform an evaluation of a given set of test specimens in a reasonable length of time with a good probability of detection at a high confidence level. This criteria is governed by parameters based upon the training and experience of the technician, as well as the technical orders and procedures under which he/she must perform inspections. This is the philosophy which governed the NDT proficiency program discussed in this paper. The proficiency test was administered by the Nondestructive Testing laboratory at the San Antonio Air Logistics Center (SA-ALC), Kelly AFB, Texas. The subjects were NDT technicians of the Structural Assessment Testing (SAT) Facility located in the Engine Division of the SA-ALC
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Loss-size and Reliability Trade-offs Amongst Diverse Redundant Binary Classifiers
Many applications involve the use of binary classifiers, including applications where safety and security are critical. The quantitative assessment of such classifiers typically involves receiver operator characteristic (ROC) methods and the estimation of sensitivity/specificity. But such techniques have their limitations. For safety/security critical applications, more relevant measures of reliability and risk should be estimated. Moreover, ROC techniques do not explicitly account for: 1) inherent uncertainties one faces during assessments, 2) reliability evidence other than the observed failure behaviour of the classifier, and 3) how this observed failure behaviour alters one's uncertainty about classifier reliability. We address these limitations using conservative Bayesian inference (CBI) methods, producing statistically principled, conservative values for risk/reliability measures of interest. Our analyses reveals trade-offs amongst all binary classifiers with the same expected loss { the most reliable classifiers are those most likely to experience high impact failures. This trade-off is harnessed by using diverse redundant binary classifiers
The five-item Brief-Symptom Rating Scale as a suicide ideation screening instrument for psychiatric inpatients and community residents
<p>Abstract</p> <p>Background</p> <p>An efficient screening instrument which can be used in diverse settings to predict suicide in different populations is vital. The aim of this study was to use the five-item Brief Symptom Rating Scale (BSRS-5) as a screening instrument for the prediction of suicide ideation in psychiatric, community and general medical settings.</p> <p>Methods</p> <p>Five hundred and one psychiatric, 1,040 community and 969 general medical participants were recruited. The community participants completed a structured telephone interview, and the other two groups completed the self-report BSRS-5 questionnaire.</p> <p>Results</p> <p>The logistic regression analysis showed that the predictors of suicide ideation for the psychiatric group were depression, hostility and inferiority (<it>p </it>< 0.001, <it>p </it>= 0.016, <it>p </it>= 0.011), for the community group, inferiority, hostility and insomnia (<it>p </it>< 0.001, <it>p </it>< 0.001, <it>p </it>= 0.003), and for the general medical group, inferiority, hostility, depression and insomnia (<it>p </it>< 0.001, <it>p </it>= 0.001, <it>p </it>= 0.020, <it>p </it>= 0.008). The structural equation model showed the same symptom domains that predicted suicide ideation for all three groups. The receiver operating characteristic curve using the significant symptom domains from logistic regression showed that for the psychiatric group, the optimal cut-off point was 4/5 for the total of the significant dimensions (positive predictive value [PPV] = 78.01%, negative predictive value [NPV] = 79.05%), for the community group, 7/8 (PPV = 68.75%, NPV = 96.09%), and for the general medical group, 12/13 (PPV = 92.86%, NPV = 88.48%).</p> <p>Conclusion</p> <p>The BSRS-5 is an efficient tool for the screening of suicide ideation-prone psychiatric inpatients, general medical patients, and community residents. Understanding the discriminative symptom domains for different groups and the relationship between them can help health care professionals in their preventative programs and clinical treatment.</p
Test Data Sets for Evaluating Data Visualization Techniques
In this paper we take a step toward addressing a pressing general problem in the development of data visualization systems — how to measure their effectiveness. The step we take is to define a model for specifying the generation of test data that can be em-ployed for standardized and quantitative testing of a system’s per-formance. These test data sets, in conjunction with appropriate testing procedures, can provide a basis for certifying the effective-ness of a visualization system and for conducting comparative studies to steer system development
Risk assessment and decision making about in-labour transfer from rural maternity care: a social judgment and signal detection analysis
Background: The importance of respecting women's wishes to give birth close to their local community is supported by policy in many developed countries. However, persistent concerns about the quality and safety of maternity care in rural communities have been expressed. Safe childbirth in rural communities depends on good risk assessment and decision making as to whether and when the transfer of a woman in labour to an obstetric led unit is required. This is a difficult decision. Wide variation in transfer rates between rural maternity units have been reported suggesting different decision making criteria may be involved; furthermore, rural midwives and family doctors report feeling isolated in making these decisions and that staff in urban centres do not understand the difficulties they face. In order to develop more evidence based decision making strategies greater understanding of the way in which maternity care providers currently make decisions is required. This study aimed to examine how midwives working in urban and rural settings and obstetricians make intrapartum transfer decisions, and describe sources of variation in decision making. Methods: The study was conducted in three stages. 1. 20 midwives and four obstetricians described factors influencing transfer decisions. 2. Vignettes depicting an intrapartum scenario were developed based on stage one data. 3. Vignettes were presented to 122 midwives and 12 obstetricians who were asked to assess the level of risk in each case and decide whether to transfer or not. Social judgment analysis was used to identify the factors and factor weights used in assessment. Signal detection analysis was used to identify participants' ability to distinguish high and low risk cases and personal decision thresholds. Results: When reviewing the same case information in vignettes midwives in different settings and obstetricians made very similar risk assessments. Despite this, a wide range of transfer decisions were still made, suggesting that the main source of variation in decision making and transfer rates is not in the assessment but the personal decision thresholds of clinicians. Conclusions: Currently health care practice focuses on supporting or improving decision making through skills training and clinical guidelines. However, these methods alone are unlikely to be effective in improving consistency of decision making
Predicting Distribution of Aedes Aegypti and Culex Pipiens Complex, Potential Vectors of Rift Valley Fever Virus in Relation to Disease Epidemics in East Africa.
The East African region has experienced several Rift Valley fever (RVF) outbreaks since the 1930s. The objective of this study was to identify distributions of potential disease vectors in relation to disease epidemics. Understanding disease vector potential distributions is a major concern for disease transmission dynamics. DIVERSE ECOLOGICAL NICHE MODELLING TECHNIQUES HAVE BEEN DEVELOPED FOR THIS PURPOSE: we present a maximum entropy (Maxent) approach for estimating distributions of potential RVF vectors in un-sampled areas in East Africa. We modelled the distribution of two species of mosquitoes (Aedes aegypti and Culex pipiens complex) responsible for potential maintenance and amplification of the virus, respectively. Predicted distributions of environmentally suitable areas in East Africa were based on the presence-only occurrence data derived from our entomological study in Ngorongoro District in northern Tanzania. Our model predicted potential suitable areas with high success rates of 90.9% for A. aegypti and 91.6% for C. pipiens complex. Model performance was statistically significantly better than random for both species. Most suitable sites for the two vectors were predicted in central and northwestern Tanzania with previous disease epidemics. Other important risk areas include western Lake Victoria, northern parts of Lake Malawi, and the Rift Valley region of Kenya. Findings from this study show distributions of vectors had biological and epidemiological significance in relation to disease outbreak hotspots, and hence provide guidance for the selection of sampling areas for RVF vectors during inter-epidemic periods
Reliability and Validity of the KIPPPI: An Early Detection Tool for Psychosocial Problems in Toddlers
Background: The KIPPPI (Brief Instrument Psychological and Pedagogical Problem Inventory) is a Dutch questionnaire that measures psychosocial and pedagogical problems in 2-year olds and consists of a KIPPPI Total score, Wellbeing scale, Competence scale, and Autonomy scale. This study examined the reliability, validity, screening accuracy and clinical application of the KIPPPI. Methods: Parents of 5959 2-year-old children in the Rotterdam area, the Netherlands, were invited to participate in the study. Parents of 3164 children (53.1% of all invited parents) completed the questionnaire. The internal consistency was evaluated and in subsamples the test-retest reliability and concurrent validity with regard to the Child Behavioral Checklist (CBCL). Discriminative validity was evaluated by comparing scores of parents who worried about their child's upbringing and parent's that did not. Screening accuracy of the KIPPPI was evaluated against the CBCL by calculating the Receiver Operating Characteristic (ROC) curves. The clinical application was evaluated by the relation between KIPPPI scores and the clinical decision made by the child health professionals. Results: Psychometric properties of the KIPPPI Total score, Wellbeing scale, Competence scale and Autonomy scale were respectively: Cronbach's alphas: 0.88, 0.86, 0.83, 0.58. Test-rete
The use of a Psoroptes ovis serodiagnostic test for the analysis of a natural outbreak of sheep scab
<p>Abstract</p> <p>Background</p> <p>Sheep scab is a highly contagious disease of sheep caused by the ectoparasitic mite <it>Psoroptes ovis</it>. The disease is endemic in the UK and has significant economic impact through its effects on performance and welfare. Diagnosis of sheep scab is achieved through observation of clinical signs e.g. itching, pruritis and wool loss and ultimately through the detection of mites in skin scrapings. Early stages of infestation are often difficult to diagnose and sub-clinical animals can be a major factor in disease spread. The development of a diagnostic assay would enable farmers and veterinarians to detect disease at an early stage, reducing the risk of developing clinical disease and limiting spread.</p> <p>Methods</p> <p>Serum samples were obtained from an outbreak of sheep scab within an experimental flock (n = 480 (3 samples each from 160 sheep)) allowing the assessment, by ELISA of sheep scab specific antibody prior to infestation, mid-outbreak (combined with clinical assessment) and post-treatment.</p> <p>Results</p> <p>Analysis of pre-infestation samples demonstrated low levels of potential false positives (3.8%). Of the 27 animals with clinical or behavioural signs of disease 25 tested positive at the mid-outbreak sampling period, however, the remaining 2 sheep tested positive at the subsequent sampling period. Clinical assessment revealed the absence of clinical or behavioural signs of disease in 132 sheep, whilst analysis of mid-outbreak samples showed that 105 of these clinically negative animals were serologically positive, representing potential sub-clinical infestations.</p> <p>Conclusions</p> <p>This study demonstrates that this ELISA test can effectively diagnose sheep scab in a natural outbreak of disease, and more importantly, highlights its ability to detect sub-clinically infested animals. This ELISA, employing a single recombinant antigen, represents a major step forward in the diagnosis of sheep scab and may prove to be critical in any future control program.</p
Length of sick leave – Why not ask the sick-listed? Sick-listed individuals predict their length of sick leave more accurately than professionals
BACKGROUND: The knowledge of factors accurately predicting the long lasting sick leaves is sparse, but information on medical condition is believed to be necessary to identify persons at risk. Based on the current practice, with identifying sick-listed individuals at risk of long-lasting sick leaves, the objectives of this study were to inquire the diagnostic accuracy of length of sick leaves predicted in the Norwegian National Insurance Offices, and to compare their predictions with the self-predictions of the sick-listed. METHODS: Based on medical certificates, two National Insurance medical consultants and two National Insurance officers predicted, at day 14, the length of sick leave in 993 consecutive cases of sick leave, resulting from musculoskeletal or mental disorders, in this 1-year follow-up study. Two months later they reassessed 322 cases based on extended medical certificates. Self-predictions were obtained in 152 sick-listed subjects when their sick leave passed 14 days. Diagnostic accuracy of the predictions was analysed by ROC area, sensitivity, specificity, likelihood ratio, and positive predictive value was included in the analyses of predictive validity. RESULTS: The sick-listed identified sick leave lasting 12 weeks or longer with an ROC area of 80.9% (95% CI 73.7–86.8), while the corresponding estimates for medical consultants and officers had ROC areas of 55.6% (95% CI 45.6–65.6%) and 56.0% (95% CI 46.6–65.4%), respectively. The predictions of sick-listed males were significantly better than those of female subjects, and older subjects predicted somewhat better than younger subjects. Neither formal medical competence, nor additional medical information, noticeably improved the diagnostic accuracy based on medical certificates. CONCLUSION: This study demonstrates that the accuracy of a prognosis based on medical documentation in sickness absence forms, is lower than that of one based on direct communication with the sick-listed themselves
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